Learning Jupyter
Learn how to write code, mathematics, graphics, and output, all in a single document, as well as in a web browser using Project Jupyter


• Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide

• This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease

• This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc

This book caters to all developers, students, or educators who want to execute code, see output, and comment all in the same document, in the browser. Data science professionals will also find this book very useful to perform technical and scientific computing in a graphical, agile manner.


• Install and run the Jupyter Notebook system on your machine

• Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook

• Use interactive widgets to manipulate and visualize data in real time

• Start sharing your Notebook with colleagues

• Invite your colleagues to work with you in the same Notebook

• Organize your Notebook using Jupyter namespaces

• Access big data in Jupyter

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more.

This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we'll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode.

Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.

This comprehensive practical guide will teach you how to work with the Jupyter Notebook system. It demonstrates the integration of various programming languages with Jupyter Notebook through hands-on examples in every chapter.

1124015385
Learning Jupyter
Learn how to write code, mathematics, graphics, and output, all in a single document, as well as in a web browser using Project Jupyter


• Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide

• This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease

• This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc

This book caters to all developers, students, or educators who want to execute code, see output, and comment all in the same document, in the browser. Data science professionals will also find this book very useful to perform technical and scientific computing in a graphical, agile manner.


• Install and run the Jupyter Notebook system on your machine

• Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook

• Use interactive widgets to manipulate and visualize data in real time

• Start sharing your Notebook with colleagues

• Invite your colleagues to work with you in the same Notebook

• Organize your Notebook using Jupyter namespaces

• Access big data in Jupyter

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more.

This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we'll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode.

Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.

This comprehensive practical guide will teach you how to work with the Jupyter Notebook system. It demonstrates the integration of various programming languages with Jupyter Notebook through hands-on examples in every chapter.

43.99 In Stock
Learning Jupyter

Learning Jupyter

by Dan Toomey
Learning Jupyter

Learning Jupyter

by Dan Toomey

eBook

$43.99 

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Overview

Learn how to write code, mathematics, graphics, and output, all in a single document, as well as in a web browser using Project Jupyter


• Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide

• This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease

• This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc

This book caters to all developers, students, or educators who want to execute code, see output, and comment all in the same document, in the browser. Data science professionals will also find this book very useful to perform technical and scientific computing in a graphical, agile manner.


• Install and run the Jupyter Notebook system on your machine

• Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook

• Use interactive widgets to manipulate and visualize data in real time

• Start sharing your Notebook with colleagues

• Invite your colleagues to work with you in the same Notebook

• Organize your Notebook using Jupyter namespaces

• Access big data in Jupyter

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more.

This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we'll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode.

Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.

This comprehensive practical guide will teach you how to work with the Jupyter Notebook system. It demonstrates the integration of various programming languages with Jupyter Notebook through hands-on examples in every chapter.


Product Details

ISBN-13: 9781785889455
Publisher: Packt Publishing
Publication date: 11/30/2016
Sold by: Barnes & Noble
Format: eBook
Pages: 238
File size: 14 MB
Note: This product may take a few minutes to download.

About the Author

Dan Toomey has been developing applications for over 20 years. He has worked in a variety of industries and size companies in roles from sole contributor to VP/CTO level. For the last 10 years or so, he has been contracting to companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Again, as a contractor developer in the area. Dan has also written R for Data Sciences with Packt Publishing.
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